chore: import upstream snapshot with attribution

2026-07-13 13:33:03 +08:00
commit 5b57521aa1
8226 changed files with 3425766 additions and 0 deletions
@@ -0,0 +1,62 @@
+//
+//  ShapeSetDiff1D.cpp
+//  MNN
+//
+//  Created by MNN on 2021/06/24.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include <set>
+#include "shape/SizeComputer.hpp"
+#include "core/Macro.h"
+
+namespace MNN {
+
+class ShapeUnique : public SizeComputer {
+    virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
+                               const std::vector<Tensor*>& outputs) const override {
+        MNN_ASSERT(1 == inputs.size());
+        if (inputs[0]->getType().bytes() != 4) {
+            return false;
+        }
+        auto& ib = inputs[0]->buffer();
+        auto& ob = outputs[0]->buffer();
+        ob.dimensions = 1;
+        TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+        ob.type = ib.type;
+        if (inputs[0]->host<int32_t>() == nullptr) {
+            return false;
+        }
+        std::set<int> values;
+        auto eleSize = inputs[0]->elementSize();
+        for (int i = 0; i < eleSize; i++) {
+            values.insert(inputs[0]->host<int32_t>()[i]);
+        }
+        ob.dim[0].extent = values.size();
+        if (outputs.size() > 1) {
+            outputs[1]->buffer().dimensions = 1;
+            outputs[1]->buffer().dim[0].extent = outputs.size() <= 2 ? eleSize : (int)values.size();
+            TensorUtils::getDescribe(outputs[1])->dimensionFormat =
+                TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+            outputs[1]->buffer().type = halide_type_of<int>();
+        }
+        if (outputs.size() > 2) {
+            outputs[2]->buffer().dimensions = 1;
+            outputs[2]->buffer().dim[0].extent = eleSize;
+            TensorUtils::getDescribe(outputs[2])->dimensionFormat =
+                TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+            outputs[2]->buffer().type = halide_type_of<int>();
+        }
+        if (outputs.size() > 3) {
+            outputs[3]->buffer().dimensions = 1;
+            outputs[3]->buffer().dim[0].extent = (int)values.size();
+            TensorUtils::getDescribe(outputs[3])->dimensionFormat =
+                TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+            outputs[3]->buffer().type = halide_type_of<int>();
+        }
+        return true;
+    }
+};
+
+REGISTER_SHAPE_INPUTS(ShapeUnique, OpType_Unique, std::vector<int>({0}));
+} // namespace MNN